• Architect and implement cloud-native, production-grade APIs designed for scale, performance, and resilience. • Lead and guide engineering teams in technical decisions, best practices, and long-term architecture strategies. • Collaborate across product, operations, and engineering to translate requirements into well-designed features and scalable services. • Write clean, efficient, and testable code using languages like Golang and Java. • Design and execute robust unit, integration, and performance test suites to ensure product reliability. • Participate in and lead Agile ceremonies including stand-ups, planning, refinement, and retrospectives. • Drive adoption of DevOps and CI/CD methodologies to support rapid development and reliable deployment pipelines. • Act as a mentor to junior engineers, elevating the overall technical expertise of the team. • Serve as a problem-solver and unblocker on complex technical challenges.

• Design, build, and operate streaming services on Kafka, Spring Boot, and Spring Cloud Stream — directing agents to scaffold, test, and iterate, and owning the outcome end-to-end. • Develop and manage Kafka connectors for data integration (DynamoDB, S3, NSQ, custom sinks/sources) and the SMT chains that keep them honest. • Own schema management and evolution across Protobuf, Schema Registry, and multi-language code generation — including the Gradle/Nexus publishing pipelines that back it. • Drive platform migrations (MSK → Confluent Cloud, NSQ → Kafka) including dual-cluster consumer patterns, VPC peering, and cutover playbooks. • Build monitoring, alerting, and operational tooling (DataDog, PagerDuty, Prometheus) that catch problems before pages fire. • Write infrastructure as code in Terraform, ship it through CI/CD, and participate in the on-call rotation and incident response for the services you own. • Work AI-natively as the default mode of operation. Run multiple agents in parallel. Write prompts with real context and constraints. Review every diff like you wrote it yourself. Know when to throw the agent's output out and do it by hand. • Evolve the team's AI-native practices — prompt libraries, evals, review rituals, and the guardrails that make all of it safe at production scale. • Mentor teammates, raise the bar on technical standards, and contribute to the team's API design, data contracts, and integration patterns.

• Work closely with cost and performance cross-functional partners and engineers across all teams at Airbnb to optimize the performance and the operating cost of our infrastructure. • Work with our largest services to optimize their performance through profiling, analysis and tuning. • Build distributed performance tooling to constantly collect performance data and develop automation to surface performance bottlenecks. • Lead continuous load testing in production to determine performance bottlenecks and vulnerabilities of airbnb.com. • Work on production performance issues to minimize latency for our customers. • Work to modernize Airbnb’s software stack touching every layer. • Build infrastructure to deploy the latest hardware to our AWS Kubernetes clusters in order to minimize their footprint.

• Maintain, enhance, and refactor existing backend applications and services • Analyze existing codebases and implement functional and technical improvements • Develop and maintain backend components and APIs using Python and/or Node.js • Support integrations with SAP BTP and SAP-adjacent systems (APIs, services, extensions) • Apply secure coding practices and address vulnerabilities in existing applications • Improve application performance, reliability, and maintainability • Investigate and resolve incidents, defects, and production issues • Contribute to documentation, technical analysis, and knowledge transfer • Collaborate with SAP, infrastructure, and product teams in an international environment • Support gradual modernization and automation initiatives when applicable